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finmath lib is a Mathematical Finance Library in Java.
It provides algorithms and methodologies related to mathematical finance.
/*
* (c) Copyright Christian P. Fries, Germany. Contact: [email protected].
*
* Created on 09.02.2004
*/
package net.finmath.montecarlo;
import java.io.IOException;
import java.io.Serializable;
import org.apache.commons.lang3.Validate;
import net.finmath.functions.NormalDistribution;
import net.finmath.randomnumbers.MersenneTwister;
import net.finmath.stochastic.RandomVariable;
import net.finmath.time.TimeDiscretization;
/**
* Implementation of a time-discrete n-dimensional Brownian motion
* W = (W1,...,Wn) where Wi is
* a Brownian motion and Wi, Wj are
* independent for i not equal j.
*
* For a correlated Brownian motion with see
* {@link net.finmath.montecarlo.CorrelatedBrownianMotion}.
*
* Here the dimension n is called factors since this Brownian motion is used to
* generate multi-dimensional multi-factor Ito processes and there one might
* use a different number of factors to generate Ito processes of different
* dimension.
*
* The quadruple (time discretization, number of factors, number of paths, seed)
* defines the state of an object of this class, i.e., BrownianMotionLazyInit for which
* there parameters agree, generate the same random numbers.
*
* The class is immutable and thread safe. It uses lazy initialization.
*
* @author Christian Fries
* @version 1.6
*/
public class BrownianMotionFromMersenneRandomNumbers implements BrownianMotion, Serializable {
private static final long serialVersionUID = -5430067621669213475L;
private final TimeDiscretization timeDiscretization;
private final int numberOfFactors;
private final int numberOfPaths;
private final int seed;
private final RandomVariableFactory randomVariableFactory;
private transient RandomVariable[][] brownianIncrements;
private transient Object brownianIncrementsLazyInitLock = new Object();
/**
* Construct a Brownian motion.
*
* The constructor allows to set the factory to be used for the construction of
* random variables. This allows to generate Brownian increments represented
* by different implementations of the RandomVariable (e.g. the RandomVariableFromFloatArray internally
* using float representations).
*
* @param timeDiscretization The time discretization used for the Brownian increments.
* @param numberOfFactors Number of factors.
* @param numberOfPaths Number of paths to simulate.
* @param seed The seed of the random number generator.
* @param randomVariableFactory Factory to be used to create random variable.
*/
public BrownianMotionFromMersenneRandomNumbers(
final TimeDiscretization timeDiscretization,
final int numberOfFactors,
final int numberOfPaths,
final int seed,
final RandomVariableFactory randomVariableFactory) {
super();
Validate.isTrue(numberOfFactors > 0, "Number of factors must be greater or equal 1 (given %d).", numberOfFactors);
Validate.isTrue(numberOfPaths > 0, "Number of paths must be greater or equal 1 (given %d).", numberOfPaths);
this.timeDiscretization = timeDiscretization;
this.numberOfFactors = numberOfFactors;
this.numberOfPaths = numberOfPaths;
this.seed = seed;
this.randomVariableFactory = randomVariableFactory;
brownianIncrements = null; // Lazy initialization
}
/**
* Construct a Brownian motion.
*
* @param timeDiscretization The time discretization used for the Brownian increments.
* @param numberOfFactors Number of factors.
* @param numberOfPaths Number of paths to simulate.
* @param seed The seed of the random number generator.
*/
public BrownianMotionFromMersenneRandomNumbers(
final TimeDiscretization timeDiscretization,
final int numberOfFactors,
final int numberOfPaths,
final int seed) {
this(timeDiscretization, numberOfFactors, numberOfPaths, seed, new RandomVariableFromArrayFactory());
}
@Override
public BrownianMotion getCloneWithModifiedSeed(final int seed) {
return new BrownianMotionFromMersenneRandomNumbers(getTimeDiscretization(), getNumberOfFactors(), getNumberOfPaths(), seed);
}
@Override
public BrownianMotion getCloneWithModifiedTimeDiscretization(final TimeDiscretization newTimeDiscretization) {
/// @TODO This can be improved: a complete recreation of the Brownian motion wouldn't be necessary!
return new BrownianMotionFromMersenneRandomNumbers(newTimeDiscretization, getNumberOfFactors(), getNumberOfPaths(), getSeed());
}
@Override
public RandomVariable getIncrement(final int timeIndex, final int factor) {
return getBrownianIncrement(timeIndex, factor);
}
@Override
public RandomVariable getBrownianIncrement(final int timeIndex, final int factor) {
// Thread safe lazy initialization
synchronized(brownianIncrementsLazyInitLock) {
if(brownianIncrements == null) {
doGenerateBrownianMotion();
}
}
/*
* We return an immutable object which ensures that the receiver does not alter the data.
*/
return brownianIncrements[timeIndex][factor];
}
/**
* Lazy initialization of brownianIncrement. Synchronized to ensure thread safety of lazy init.
*/
private void doGenerateBrownianMotion() {
if(brownianIncrements != null) {
return; // Nothing to do
}
// Create random number sequence generator
final MersenneTwister mersenneTwister = new MersenneTwister(seed);
// Allocate memory
final double[][][] brownianIncrementsArray = new double[timeDiscretization.getNumberOfTimeSteps()][numberOfFactors][numberOfPaths];
// Pre-calculate square roots of deltaT
final double[] sqrtOfTimeStep = new double[timeDiscretization.getNumberOfTimeSteps()];
for(int timeIndex=0; timeIndex